An Efficient Large-Scale Volume Data Compression Algorithm

Authors:
Degui Xiao;Liping Zhao;Lei Yang;Zhiyong Li;Kenli Li
Affiliations:
School of Computer and Communication, Hunan University, Changsha, China 410082;School of Computer and Communication, Hunan University, Changsha, China 410082 and School of Information Engineering, Jiaxing University, Jiaxing, China 314000;School of Computer and Communication, Hunan University, Changsha, China 410082;School of Computer and Communication, Hunan University, Changsha, China 410082;School of Computer and Communication, Hunan University, Changsha, China 410082
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Year:
2009

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Abstract

Considering empty region in the volumetric data occupying a certain percentage, an efficient large-scale data compression algorithm based on VQ is presented. Firstly, the entire volume data are divided into many smaller regular blocks, and the blocks are classified into two groups according to their average gradient values: one consists of those blocks with zero average gradient value, and the other consists of those with non-zero average gradient values. Secondly, only those blocks with non-zero average gradient values are decomposed into a three hierarchical representation and vector quantized. Finally, block data in different groups are reconstructed with different ways. When applying this algorithm to the volume data, all experimental results demonstrate the proposed algorithm is more efficient than most existing large-scale volume data compression algorithms.